Day6 呦呦鹿鸣—学习R包

options("repos" = c(CRAN="https://mirrors.tuna.tsinghua.edu.cn/CRAN/")) #对应清华源
options(BioC_mirror="https://mirrors.ustc.edu.cn/bioc/") #对应中科大源

test <- iris[c(1:2,51:52,101:102),]

mutate(test, new = Sepal.Length * Sepal.Width)
mutate(df, z = x + y)

select(test,1)# 筛选test数据集的第一列
iris %>% select(1:3)# 筛选iris数据集的第一到第三列

select(test, Petal.Length, Petal.Width)
iris %>% select(Species, Sepal.Length)

filter(test, Species == "setosa")
starwars %>% filter(species == "Human")

arrange(test, Sepal.Length)#默认从小到大排序
mtcars %>% arrange(cyl, disp)

summarise(test, mean(Sepal.Length), sd(Sepal.Length)) # 计算Sepal.Length的平均值和标准差
summarise(group_by(test, Species),mean(Sepal.Length), sd(Sepal.Length))  # 先按照Species分组，计算每组Sepal.Length的平均值和标准差

test %>% group_by(Species) %>%  summarise(mean(Sepal.Length), sd(Sepal.Length))

count(test,Species)

inner_join(test1, test2, by = "x")

left_join(test1, test2, by = 'x')
left_join(test2, test1, by = 'x')

full_join( test1, test2, by = 'x')

semi_join(x = test1, y = test2, by = 'x')

anti_join(x = test2, y = test1, by = 'x')

bind_rows(test1,test2)函数需要两个表格列数相同
bind_cols(test1,test2)函数则需要两个数据框有相同的行数